Local Outlier Factor (LOF) is based on a concept of a local density. Local density is estimated by the typical distance at which a point can be “reached” from its neighbors. The definition of “reachability distance” used in LOF is an additional measure to produce more stable results within clusters. It is able to identify outliers in a data set that would not be outliers in another area of the data set. LOF is only applicable to low-dimensional vector spaces, the algorithm can be applied in any context a dissimilarity function can be defined.